Back

First nationwide mosquito surveillance in Northern Irish wetlands reveals presence of Culex pipiens/molestus hybrids

Carmichael, R. M.; Kirby, G.; Sloan, L.; Desjardins, A.; Parvy, J.-P.; Baldini, F.; Pondeville, E.; Dick, J. T. A.; Ferguson, H. M.; Cuthbert, R. N.

2026-10-09 ecology
10.64898/2026.10.08.757519 bioRxiv
Show abstract

While mosquito invasions and associated pathogens are increasingly prominent in Europe, evidence gaps remain for many northerly regions where proactive management interventions may be most effective. At the regional periphery of Europe, there remains a significant knowledge gap concerning mosquito vector distributions in Northern Ireland. This study aimed to address this major gap by systematically surveying larval and adult mosquito populations in key habitats (ponds, reedbeds, saltmarsh, wet grasslands, wet woodlands, and urban gardens). We further identified environmental drivers of important vector species abundance and screened collected specimens with molecular techniques to identify presence of cryptic human-biting vector species. In Northern Ireland, mosquitoes (including potential bridge vectors of West Nile and Usutu viruses) were found to be widely distributed. Between May and August 2025, a total of 2430 mosquitoes (951 adults and 1479 larvae) were collected over 196 trap nights and 76 larval collections. Collections encompassed 17 species, with Culex pipiens/torrentium being the most widely distributed and abundant taxon recorded. Mosquito abundances were greatest in reedbed habitats, related negatively with rainfall and peaked in June and July. A subset of Culex pipiens/torrentium mosquitoes were identified to species/biotype level using PCR, with the majority (89.3%) identified as Culex pipiens pipiens and 9.3% as Culex torrentium. Importantly, the first detections of Culex pipiens/molestus hybrids (1.8%) on the island of Ireland were found. This work underscores the wide, yet previously undocumented abundance and distribution of potential zoonotic vectors in Northern Ireland and provides an important baseline for management planning and future research, while contributing to broader understandings of environmental population drivers and distributions.

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.